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Neonatal and fetal growth charts to identify preterm infants less than 30 weeks gestation at risk of adverse outcomes

American Journal of Obstetrics and Gynecology May 12, 2018

Boghossian NS, et al. - Using neonatal and fetal growth charts, the researchers intended to assess and compare the power of birth weight for gestational age to predict adverse neonatal outcomes. According to the findings obtained, neither the neonatal nor the fetal growth charts were predictive of adverse newborn in-hospital outcomes. Use of the neonatal charts resulted in stronger relationships between small for gestational age and adverse outcomes in contrast to fetal charts.

Methods
  • For this investigation, the researchers studied inborn singleton infants from 2006-2014 with gestational age between 22 and 29 weeks and enrolled at one of the 852 U.S. centers participating in Vermont Oxford Network.
  • Mortality, necrotizing enterocolitis, severe intraventricular hemorrhage, severe retinopathy of prematurity, and chronic lung disease were the included outcomes.
  • They used receiver operating characteristic curve analysis to evaluate the predictive power of birth weight for gestational age, either as a score or as small for gestational age indicator, using the four charts.
  • In addition, the relative risks of the outcomes comparing small for gestational age and non-small for gestational age infants were examined using the four charts.

Results
  • When using the fetal growth charts, the percentage of small for gestational age newborns ranged between 25.9% and 29.7%.
  • When using the neonatal charts, the percentage was 10%.
  • They observed that the areas under the receiver operating characteristic curves were similar across the four classification methods and were all below 0.60, which suggests a poor predictive power.
  • Small for gestational age status, as classified by the neonatal chart, demonstrated stronger relationships with mortality, necrotizing enterocolitis, severe retinopathy of prematurity, and chronic lung disease than those based on the other classification methods.
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